Sustainable Reverse Logistics for Household Plastic Waste

This thesis investigates plastic waste recycling from a sustainable reverse logistics angle. The aim is to analyse the collection, separation and treatments systems of plastic waste and to propose redesigns for the recycling system using quantitative decision support models.

The plastic waste recycling problem is studies at three decision levels: municipal, regional, and global. Decision support systems are developed based on optimization techniques to explore the power of mathematical modelling to assist in the decision-making process. Analysis results from different decision levels show that on one decision level, models can help to find the “best option”. When combining decision levels, however, it is difficult to find one “best option" that fits all, as there are contradictory results when looking at the same factor from different decision levels. Through decision support models, this research provided clear insights into the trade-offs and helped to quantify the differences and identify key factors to determine the differences.